Short Courses
Live with Data:Basic Statistical Analysis (RA Training #3)
Date and Time: Feb 28, 2014, 1pm-4pm
Instructor: Dr. Xiaohui Wang
Room: MAGC 2.202
Abstract: Topics will include Writing research questions (RQs), Understanding data and connecting them to RQs, Basic statistical analysis for different data and RQs, Continuing training on SPSS. Pre-requisites: Live with Data: RA Training #1 and #2, Data Input & Pre-processing, Data Preparation and Exploratory Data Analysis, and Strong desire to conduct research that utilizes quantitative data analysis.
Prerequisites: None
Interpretation of SPSS Regression Diagnostics Outputs: Outliers and Influential Points
Date and Time: TBA, 2014
Instructor: Dr. James Curts
Room: TBA
Abstract: None
Prerequisites: None
| Date/Time | Instructor | Title | Room | Prerequisites | Prerequisites |
|---|---|---|---|---|---|
| TBA, 2014 | Dr. Xiaohui Wang | Introduction to SAS | TBA | Data Sets: Dataset 1, Ex Dataset #1, Ex Dataset #2, Ex Dataset #3, Ex Dataset #4, CalmTrait. |
|
| Feb 7, 2014, 1pm-4pm | Dr. Xiaohui Wang | Live with Data: Data Pre-paration and Exploratory Data Analysis (RA Training #2) | MAGC 2.202 | Abstract: Topics include Continuing training on Excel and SPSS, Pre-processing and screening procedures, Handling of missing data, Data transformation, and Exploratory data analysis using graphical techniques. Pre-requisites: Live with Data: RA Training #1 -- Data Input & Pre-processing, Basic understanding of statistics, and Strong desire to conduct research that utilizes quantitative data analysis. | |
| Dec 13, 2013, 1pm-3pm | Dr. Xiaohui Wang | Live with Data: Data Input and Pre-processing (RA Training #1) | MAGC 2.202 | Topics include introduction to Excel, hands-on data input from scratch, get organized with data files, introduction to R and SPSS, potential pre-processing procedures. | Basic understanding of statistics. Strong desire to conduct research that utilizes quantitative data analysis. |
| Oct 15, 2013, 1pm-2pm | Dr. Xiaohui Wang | An Introduction to SPSS (3rd Edition) | EDUC 3.224 | This will be a short introduction of SPSS on doing descriptive statistics for different types of data (both quantitative and qualitative data) and some basic hypothesis testing procedures. Examples of graphs/tables construction will also be discussed for presenting work in research paper. Participants will have hand-on experience during the class. | None |
| Apr 26, 2013, 2-4pm | Dr. Darrin Roger | Introduction to R (II): Powerful, Flexible Data Analysis (R is free!) | MAGC 2.202 | See above. | The above Course on April 19, and basic knowledge on stat. |
| Apr 25, 2013, noon-1pm | Dr. Xiaohui Wang | How to Choose Proper Statistical Methodology? | MAGC 2.202 | Researchers from various disciplines use statistical methodologies in their quantitative research. It is critical to choose proper statistical methodology for your specific research question. Topics such as explanation of variables, formation of research questions, flow charts on how to choose proper statistical methodology will be included. | Basic stat knowledge, and desire to do (quantitative) research. |
| Apr 19, 2013, 2-4pm | Dr. Darrin Roger | Introduction to R (I): Powerful, Flexible Data Analysis (R is free!) | MAGC 2.202 | The R data analysis system is fast becoming the standard in many fields, and for good reason: it is extremely flexible and powerful. It’s also free (both “free as in beer” and “free as in speech”). The base system can do a great many things any researcher needs to do, and there are thousands of add-ons, developed by other researchers, available at the push of a few buttons. Just about anything one might want to do with data or statistics, including most cutting-edge procedures, is possible—and sometimes quite easy—in R. The learning curve, however, can seem steep. It’s not quite as easy to get started with as SPSS, SAS, etc. This course will introduce you to R, show you how to do many basic tasks necessary to accomplish a variety of day-to-day tasks, and get you started analyzing data. There will be a strong emphasis on hands-on learning and practical applications, so feel free to send “requests” to Darrin before the course begins. The course will not make you an R wizard, but it is hoped that you will come to understand that you do not need to be one in order to analyze your data with R. | Basic knowledge on stat. |
| Nov 14, 2012, 3pm-4pm | Dr. Xiaohui Wang | Know Your Variables and Explore with SPSS | MAGC 2.202 | The course will focus on how to examine and understand your to-be-studied variables. This course will also provide a short introduction of SPSS on doing descriptive statistics for different types of data (both quantitative and qualitative data) and some basic hypothesis testing procedures. Participants will have hand-on experience during the class. | None |
| April 1, 2011, 11:45am-12:45pm | Dr. Xiaohui Wang | An Introduction to SPSS (2nd Edition) | MAGC 2.202 | This will be a short introduction of SPSS on doing descriptive statistics for different types of data (both quantitative and qualitative data) and some basic hypothesis testing procedures. Examples of graphs/tables construction will also be discussed for presenting work in research paper. Participants will have hand-on experience during the class. | None |
| April 5, 2011, 11:00am-12noon | Dr. George Yanev | From the Garden of Branching Stochastic Processes | MAGC 1.410 | Branching processes are a well developed and powerful modeling set of tools in the area of applied probability and statistics. After providing some theoretical background, we will discuss applications in biology, epidemiology, and medical sciences. | None |
| April 14, 2011, 12noon-1:30pm | Dr. Darrin Rogers | An Introduction to Statistics in R | MAGC 1.410 | Interested in free and open source software (FOSS)? Looking for a way to build and automate customized data management and analysis systems? Unwilling to pay the high fees of commercial packages? In this short course, participants will learn about the free, open-source statistical platform called R, perhaps the most widely-used statistics package on earth. We will start from the beginning: where to download it, how to install it, and then the basics of how it can be used for statistical analysis and data management. We will focus on what you need to know to get started, where to find help, and how to recognize and correct some of the most common errors. Some advantages and disadvantages of R compared to commercial packages (especially SPSS) will be pointed out along the way. The presenter is not an R expert; only someone who’s been using it for a couple of years. He can’t give you answers to all of your questions, but he’ll try to point you to the resources that can. Bring a personal laptop with a working wireless connection if you’d like to install R and participate in the demonstrations. | Basic statistical knowledge; moderate proficiency with personal computers. It will be nice to have your personal laptop to use during the short course. |
| Mar 03, 2010, 2:30-3:30pm | Dr. George Yanev | Statistical Consulting: Common Practices and Challenges | MAGC 1.302 | In a statistical consultation, you seek the help of a statistician to select and use the best methods for obtaining and analyzing data for some data-related objective. Usually the objective is to answer a question. The subject area could be almost anything, such as business, education, management, government, agriculture, economics, or a science. We will discuss questions as: •Do you need a statistical consultant? •Roles of a statistical consultant •How to involve a statistical consultant? •Typical project cycle. •Undergraduate consulting. | None |
| Mar 05, 2010, 12:45-1:45pm | Dr. Xiaohui Wang | An Introduction to SPSS | MAGC 2.202 | This will be a short introduction of SPSS on doing descriptive statistics for different types of data (both quantitative and qualitative data) and some basic hypothesis testing procedures. Examples of graphs/tables construction will also be discussed for presenting work in research paper. Participants will have hand-on experience during the class. | None |
| Mar 05, 2010, 2:00-3:00pm | Dr. Jaime Curts | An Introduction to Non-linear Smoothing Methods | MAGC 2.202 | Non parametric methods for estimating local regression surfaces allows greater flexibility than traditional modeling tools in the absence of a suitable parametric model or when there are outliers in the data and a robust fitting methods is necessary. Assume that for i = 1 to n, the ith measurement yi of the response y and the corresponding measurement xi of the vector x of p predictors are related by yi = g(xi) + ei where g is the regression function and ei is a random error. The idea of local regression is that near x = x0, the regression function g(x) can be locally approximated by the value of a function in some specified parametric class. Such a local approximation is obtained by fitting a regression surface to the data points within a chosen neighborhood of the point x0. | Participants with previous knowledge of regression analysis |
| Nov 16, 2010, 4:05-5:05pm | Dr. Santanu Chakraborty | Some interesting properties of Dirichlet distributions with applications | MAGC 2.402 | Dirichlet distribution is the multivariate generalization of the beta distribution. It is known as the conjugate to the multinomial distribution in Bayesian statistics. One can generate this distribution starting from Polya’s urn. Suppose the urn has balls of k different colors. Let there be n1 balls of color 1, n2 balls of color 2, …, nk balls of color k. Now if we perform N draws from the urn and after each draw, the ball is placed back in to the urn with an additional ball of the same color. In the limit as N goes to infinity, the proportions of different colored balls in the urn will be distributed as a Dirichlet distribution. Dirichelet distribution has many interesting properties and several nice applications. In this course, we will give an overview of the Dirichlet distribution and will briefly mention Dirichlet process. | Some previous knowledge on well known univariate discrete and continuous distributions. |
| Nov 22, 2010, 11:45-12:45pm | Dr. Xiaohui Wang | Flow Charts for Conducting Research Project and Collaboration with Statistician | MAGC 1.202 | Conducing research is one of most enjoyable things a scholar does for his or her career. Research is the search for knowledge or any systematic investigation to establish facts, so there are proper procedures to conduct research by a researcher or a team of researchers. The flow chart describes the guideline for proper steps. Emphasized items include knowing what you want, how to plan your research, and how to form research questions, etc. Interdisciplinary collaboration is needed in almost all of research projects. This short course also shows flow chart and exemplary works on how to collaborate with statistician to boost research quality. | This course is for current or future researchers. |